## Reinforcement Learning - Monte Carlo Methods

Part 2 of the RL series. A slightly deeper dive into reinforcement learning methods by learning how to use Monte Carlo simulations to learn how to play blackjack.

Click to read and post commentsPart 2 of the RL series. A slightly deeper dive into reinforcement learning methods by learning how to use Monte Carlo simulations to learn how to play blackjack.

Click to read and post commentsThe first part in a series introducing the theory, math and implementation details of reinforcement learning algorithms using Python. Here we introduce the topic with a very simple RL problem, the n-armed bandit problem.

Click to read and post commentsA gentle introduction to the powerful machine learning library, Theano.

Click to read and post commentsA brief addendum to my previous post on a simple genetic algorithm. Here I explore how varying the parameters affects our GA performance.

Click to read and post commentsA beginner tutorial for an even simpler recurrent neural network implementation in Julia.

Click to read and post commentsHere I'm going to revisit backpropagation theory by thinking about neural networks as computational graphs upon which we can easily visualize the chain rule to compute partial derivatives.

posted at 00:00
by Brandon Brown
· Computational Graphs

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